This invention relates to a system and method for acoustically detecting tool break events in machining operations that produce major cutting condition changes occurring over a period of time.
Significant breakage of a cutting insert, threatening immediate damage to the workpiece or machine tool or serious enough to force a recut, and evidenced by a large and abrupt change in cutting noise that persists for a minimum confirmation period, is detected as disclosed in application Ser. No. 664,188 filed Oct. 24, 1984, C. E. Thomas et al, "Acoustic Monitoring of Cutting Conditions to Detect Tool Break Events". A high frequency vibration sensor monitors both acoustic emissions produced by tool fracture and cutting vibration noise. A microcomputer analyzes the processed vibration signal via amplitude-time domain pattern recognition techniques to separate major tool break events from both minor tool break events and various sources of potential false alarms. The acoustic frequency band is chosen to discriminate against lower frequency machinery noise below about 30 KHz and avoid the use of high frequencies above 100 KHz. A broken tool alarm to stop cutting is not issued on a detected abrupt increase or decrease in signal level unless a persistent change in cutting noise indicates a substantial change in cutting conditions.
Extensive machining experiments have shown that large changes in cutting noise level and cutting conditions due to tool break events do not always occur abruptly in a single step increase or decrease. The total change may take place more gradually, or as a series of small abrupt steps. Changes of these latter two types may fail to meet the break detection criteria of the system of Ser. No. 664,188, but may accompany tool break events capable of significantly damaging a workpiece. A system is needed for detecting these less sudden cutting condition changes without introducing a significant increase in false alarm rate.
Another related copending application is Ser. No. 664,189, filed Oct. 24, 1984, Thomas et al, "Acoustic Detection of Tool Break Events in Machine Tool Operations". This approach generally relies on detecting the tool fracture signal before checking for a cutting noise signal change. The pattern recognition logic makes a three step check of the processed vibration signal before generating an alarm. A positive-going signal transient that may have its source in a break event triggers a mean shift detector to check for a change in cutting noise; if the mean shift persists for a given period the alarm is set off. The present system uses the same acoustic sensor and analog signal processing as these copending applications, but like the first emphasizes detection and interpretation of changes in the cutting noise, rather than detection of acoustic emissions produced by tool fracture.